. clear
{\smallskip}
. set seed 999
{\smallskip}
. quietly set obs 1600
{\smallskip}
. generate x1 = invnormal(uniform())
{\smallskip}
. generate x2 = invnormal(uniform())
{\smallskip}
. generate ue = invexponential(0.6, uniform())
{\smallskip}
. generate we = invexponential(1.4, uniform())
{\smallskip}
. generate v = invnormal(uniform())
{\smallskip}
. generate y = x1 + 2 * x2 - ue + we + v
{\smallskip}
. sftt y x1 x2, nocons
{\smallskip}
initial:       log likelihood = -3233.1231
rescale:       log likelihood = -3233.1231
rescale eq:    log likelihood = -3229.7914
Iteration 0:   log likelihood = -3229.7914  
Iteration 1:   log likelihood = -3170.7503  (not concave)
Iteration 2:   log likelihood = -3161.2028  
Iteration 3:   log likelihood = -3161.0853  
Iteration 4:   log likelihood = -3161.0851  
{\smallskip}
{\bftt{Two-tier stochastic frontier model with exponential specification}}
{\smallskip}
                                                       Number of obs =   1,600
                                                       Wald chi2(2)  = 3186.44
Log likelihood = -3161.0851                            Prob > chi2   =  0.0000
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
           y {\VBAR} Coefficient  Std. err.      z    P>|z|     [95\% conf. interval]
\HLI{13}{\PLUS}\HLI{64}
frontier_y   {\VBAR}
          x1 {\VBAR}   .9915255   .0419677    23.63   0.000     .9092703    1.073781
          x2 {\VBAR}   2.032645   .0402524    50.50   0.000     1.953751    2.111538
\HLI{13}{\PLUS}\HLI{64}
ln_sig_v     {\VBAR}
       _cons {\VBAR}  -.0712458   .0951567    -0.75   0.454    -.2577494    .1152579
\HLI{13}{\PLUS}\HLI{64}
ln_sig_u     {\VBAR}
       _cons {\VBAR}  -.4742256   .0972085    -4.88   0.000    -.6647506   -.2837005
\HLI{13}{\PLUS}\HLI{64}
ln_sig_w     {\VBAR}
       _cons {\VBAR}   .3918662   .0468007     8.37   0.000     .3001386    .4835939
\HLI{13}{\BOTT}\HLI{64}
